Data processing method, device, electronic device and storage medium

Abstract

The embodiments of the present application provide a data processing method, device, electronic device and storage medium, the method comprising: obtaining facial feature data of a user and product feature data of a facial product object; analyzing the facial product object based on the facial feature data and the product feature data to obtain a product analysis result; based on the product analysis result, screening out facial product objects that meet preset conditions; and being able to recommend facial products that are more suitable for the user.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a data processing method, a data processing device, an electronic device and a storage medium. Background Art

[0002] Augmented Reality (AR) technology is a technology that cleverly integrates virtual information with the real world. It widely uses a variety of technical means such as multimedia, three-dimensional modeling, real-time tracking and registration, intelligent interaction, and sensing. It simulates computer-generated virtual information such as text, images, three-dimensional models, music, and videos, and applies them to the real world. The two types of information complement each other, thereby achieving "enhancement" of the real world.

[0003] Currently, AR technology can be used to combine the virtual three-dimensional structure of the product with the user's body during the user's shopping process, making it easier for the user to purchase the product. For example, when a user is shopping for glasses, the user can select the corresponding glasses and display the virtual three-dimensional structure of the glasses on the user's face for trial wearing.

[0004] However, in the existing solutions, products are only tried on according to the user's choice, and it is impossible to recommend products that are more suitable for the user. Summary of the invention

[0005] The embodiment of the present application provides a data processing method for recommending products that are more suitable for users.

[0006] Correspondingly, an embodiment of the present application also provides a data processing device, an electronic device and a storage medium to ensure the implementation and application of the above system.

[0007] In order to solve the above problems, an embodiment of the present application discloses a data processing method, which includes: obtaining facial feature data of a user and product feature data of a facial product object; analyzing the facial product object based on the facial feature data and the product feature data to obtain a product analysis result; and screening out facial product objects that meet preset conditions based on the product analysis result.

[0008] In order to solve the above problems, an embodiment of the present application discloses a data processing method, including: obtaining facial feature data of a user and product feature data of various types of facial product objects; analyzing various types of facial product objects based on the facial feature data and the product feature data to obtain product analysis results; determining a target type that meets preset conditions based on the product analysis results, and obtaining facial product objects of the target type.

[0009] In order to solve the above problems, an embodiment of the present application discloses a data processing method, including: taking a facial image of a user and uploading it, the facial image is used to determine facial feature data, the facial feature data is used to analyze product feature data of a facial product object to determine a product analysis result, and the product analysis result is used to screen out facial product objects that match the user's facial image; receiving try-on display information corresponding to the screened-out facial product objects, the try-on display information includes a facial image of trying on the facial product object and display information of the facial product object, the display information includes product link information and product description information of the facial product object; and displaying the facial image of trying on the facial product object.

[0010] In order to solve the above problems, an embodiment of the present application discloses a data processing method, which is applied to an Internet of Things device, wherein the Internet of Things device includes an image acquisition component and a display component, and the method includes: acquiring a facial image of a user through the image acquisition component; determining facial feature data based on the facial image and uploading it, wherein the facial feature data is used to analyze the product feature data of a facial product object to determine a product analysis result, and the product analysis result is used to filter out facial product objects that match the user's facial image; receiving the filtered facial product objects; and displaying the filtered facial product objects through the display component.

[0011] In order to solve the above problems, an embodiment of the present application discloses a data processing device, including: a feature data acquisition module, used to obtain the facial feature data of a user and the product feature data of a facial product object; an analysis result acquisition module, used to analyze the facial product object based on the facial feature data and the product feature data to obtain a product analysis result; and a product object screening module, used to screen out facial product objects that meet preset conditions based on the product analysis result.

[0012] In order to solve the above problems, an embodiment of the present application discloses a data processing device, including: a feature data determination module, used to obtain the facial feature data of a user and the product feature data of various types of facial product objects; an analysis result determination module, used to analyze various types of facial product objects based on the facial feature data and the product feature data to obtain product analysis results; a product object determination module, used to determine the target type that meets preset conditions based on the product analysis results, and obtain facial product objects of the target type.

[0013] In order to solve the above problems, an embodiment of the present application discloses a data processing device, including: an image data determination module, used to take a facial image of a user and upload it, the facial image is used to determine facial feature data, the facial feature data is used to analyze the product feature data of a facial product object to determine a product analysis result, and the product analysis result is used to screen out facial product objects that match the user's facial image; a related information determination module, used to receive try-on display information corresponding to the screened facial product objects, the try-on display information includes a facial image of trying on the facial product object and display information of the facial product object, the display information includes product link information and product description information of the facial product object; a related information display module, used to display the facial image of trying on the facial product object.

[0014] In order to solve the above problems, an embodiment of the present application discloses a data processing device, which is applied to an Internet of Things device, wherein the Internet of Things device includes an image acquisition component and a display component, and the device includes: an image data acquisition module, which is used to acquire a user's facial image through the image acquisition component; an image data analysis module, which is used to determine facial feature data based on the facial image and upload it, wherein the facial feature data is used to analyze the product feature data of the facial product object to determine the product analysis result, and the product analysis result is used to screen out facial product objects that match the user's facial image; a product object receiving module, which is used to receive the screened facial product objects; and a product object display module, which is used to display the screened facial product objects through the display component.

[0015] In order to solve the above problems, an embodiment of the present application discloses an electronic device, including: a processor; and a memory, on which executable code is stored. When the executable code is executed, the processor executes one or more methods described in the above embodiments.

[0016] In order to solve the above problems, the embodiments of the present application disclose one or more machine-readable media on which executable codes are stored. When the executable codes are executed, the processor executes one or more methods described in the above embodiments.

[0017] Compared with the prior art, the embodiments of the present application have the following advantages:

[0018] In an embodiment of the present application, the facial feature data of the user and the product feature data of the facial product object can be obtained, and then the facial feature data of the user and the product feature data of the facial product object can be matched and analyzed to obtain a product analysis result, and then screening can be performed based on the product analysis result. Facial product objects that are suitable for the user's facial features can be screened out, and facial products that are more suitable for the user can be recommended to the user, making it convenient for the user to purchase. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1A is a schematic diagram of a data processing method according to an embodiment of the present application;

[0020] Figure 1B is a schematic diagram of a data processing method according to another embodiment of the present application;

[0021] Figure 2A It is a flowchart of a data processing method according to an embodiment of the present application;

[0022] Figure 2B is a schematic structural diagram of glasses according to an embodiment of the present application;

[0023] Figure 3 is a flowchart of a data processing method according to another embodiment of the present application;

[0024] Figure 4 is a flowchart of a data processing method according to another embodiment of the present application;

[0025] Figure 5 is a flowchart of a data processing method according to another embodiment of the present application;

[0026] Figure 6 is a flowchart of a data processing method according to another embodiment of the present application;

[0027] Figure 7 is a structural schematic diagram of a data processing device according to an embodiment of the present application;

[0028] Figure 8 is a structural schematic diagram of a data processing device according to another embodiment of the present application;

[0029] Fig. 9 is a structural schematic diagram of a data processing device according to another embodiment of the present application;

[0030] Fig.10 is a structural schematic diagram of a data processing device according to another embodiment of the present application;

[0031] Fig.11 It is a schematic diagram of the structure of a device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0032] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0033] The embodiments of the present application can be applied to the field of product recommendation. Product recommendation refers to introducing products in the hope that they will be accepted by users. The embodiments of the present application can be specifically applied to the recommendation scenario of facial products. The solution of the embodiments of the present application can be executed by a processing end. The processing end can be a user's terminal (mobile terminal) or a server that interacts with the terminal. Figure 1A In the example shown, the processing end is the server end. The user can use the terminal to capture the user's facial image and transmit the user's facial feature data to the server end. The server end analyzes the user's facial feature data and the product feature data of the facial products, screens out facial product objects that match the user's facial features, and recommends relevant information of the screened facial product objects (such as product links, virtual three-dimensional structures of products) and other data to the user of the terminal.

[0034] In addition to the user's terminal and the service-providing server, the processing end may also include an IoT device that can capture the user's facial image and display the trial-wearing image. For example, the processing end may also include an intelligent makeup mirror (or trial makeup mirror), which can obtain the user's facial image through the intelligent makeup mirror, and analyze the facial feature data of the facial image and the product feature data of the facial product object, filter out the facial product objects that match the user's facial features, and recommend the relevant information of the filtered facial product objects to the user. In addition, the IoT device that can capture the user's facial image and display the product object can also be used as the user's terminal to capture the user's facial image, determine the facial feature data corresponding to the facial image, and display the corresponding facial product image. For example, the user's facial image can be obtained through the IoT device, the facial feature data of the facial image can be determined, and the facial feature data can be uploaded to the server (processing end) for analysis, and the facial product objects that match the user's facial features can be filtered out. Then the server returns the relevant information of the filtered facial product objects to the IoT device, so that the facial product objects can be displayed through the IoT device.

[0035] like Figure 1BAs shown, the embodiment of the present application can be applied in the recommendation scenario of glasses. The processing end can obtain the user's facial feature data, such as the user's three-thirds and five-eyes features, the user's face shape features, the user's nose, eyebrows, eyes, skin color and other features, and then analyze the product feature data of different glasses (such as the frame height, frame color, lens color, upper edge features, lower edge features, and outer edge features of the glasses) to obtain the corresponding product analysis results, and then filter out qualified glasses (glasses suitable for the user's face) based on the product analysis results. For example, the user's facial features can be matched with the product features of the glasses to filter out glasses suitable for the user's face shape, suitable for the user's skin color, and suitable for the user's eye features, and recommend the link information of the filtered glasses to the user of the terminal to facilitate the user's purchase. For another example, the embodiment of the present application can also be applied to the recommendation scenario of facial products such as hats, face stickers, eye drills, masks, nose rings, and earrings. For example, the embodiments of the present application can be applied to a hat recommendation scenario. The processing end can obtain the user's facial feature data, such as the user's three-part and five-eye features, the user's face shape features, the user's skin color features, etc., and then combine the product feature data of different hats, such as the height of the hat, the color of the hat, the shape of the hat, etc. for analysis to obtain the corresponding product analysis results, and then screen out hats that meet the conditions and recommend them to the terminal users.

[0036] In an embodiment of the present application, the facial feature data of the user and the product feature data of the facial product object can be obtained, and then the facial feature data of the user and the product feature data of the facial product object can be matched and analyzed to obtain a product analysis result, and then screening can be performed based on the product analysis result to screen out facial product objects that are suitable for the user's facial features, and they can be recommended to the user to facilitate the user's purchase.

[0037] Specifically, the present application embodiment discloses a data processing method, which can be executed by a processing terminal, such as Figure 2A As shown, the method includes:

[0038] Step 202, obtaining the facial feature data of the user and the commodity feature data of the facial commodity object. The processing end can be the user's terminal or the server that interacts with the terminal. The embodiment of the present application can determine the facial feature data of the user based on the facial image taken. Specifically, as an optional embodiment, the step of obtaining the facial feature data includes: obtaining the facial image of the user, and identifying the facial image to obtain the facial feature data. In the case where the processing end is the user's terminal, the processing end can take the facial image of the user through a camera, and identify it to obtain the facial feature data. In the case where the processing end is the server, the process of identifying the facial image to determine the facial feature data can be performed at the terminal or at the server. Specifically, in an optional example, the facial image of the user can be taken by the camera of the terminal, and the image recognition can be performed by the terminal to obtain the facial feature data, and then the facial feature data can be uploaded to the server. In another optional example, the facial image of the user can also be taken by the camera of the terminal and uploaded to the server. After the server obtains the facial image of the user, it recognizes the facial image to obtain the facial feature data.

[0039] In addition, in addition to taking the user's facial image through the camera, multiple template images can be pre-set on the user's terminal. The user can select the template image as the user's facial image to determine the corresponding facial feature data. Specifically, as an optional embodiment, obtaining the user's facial feature data includes: determining the facial template image selected by the user, and obtaining the facial feature data of the facial template image. An image selection page can be provided on the user's terminal. In the image selection page, a switch can be set to switch the trial plan. The trial plan includes personalized trial and universal trial. Personalized trial means that the user can choose to take the user's facial image through the camera to obtain a personalized trial image; universal trial means that the user can obtain a universal trial image by selecting a pre-set template image. The user can select a facial template image similar to his or her facial features to match the facial product, which is convenient for the user to purchase.

[0040] The facial feature data in the embodiment of the present application may include one facial feature or multiple facial features, which can be set according to the needs. Specifically, as an optional embodiment, the facial feature data includes: at least one of face shape features, three-thirds and five-eyes features, eye features, nose features, forehead features, eyebrow features, and skin color features. Among them, face shape features may include oval face, round face, square face, rectangular face, prismatic face, regular triangle face, inverted triangle face, etc., three-thirds and five-eyes may include the proportion data of three-thirds and five-eyes. Eye features may include large, medium, small, etc., nose features may include wide, standard, narrow, high, collapsed, etc., and skin color features may include fair, darker, etc.

[0041] In the embodiment of the present application, the product feature data can be obtained by identifying the image of the facial product object. Specifically, as an optional embodiment, the step of obtaining the product feature data of the facial product object includes: obtaining the product image of the facial product object, and extracting the product structure data of the facial product object in the product image; based on the product structure data, determining the product feature data of the facial product object. For different products, corresponding division rules can be set on the processing end to divide the facial product object into multiple parts and identify the characteristics of each part. The product image can be obtained from the product sales page. The processing end can obtain the product image and identify the product image according to the division rules to obtain the product structure data of the facial product object, and then determine the product feature data of the facial product object based on the product structure data. In the example Figure 2B In the example shown, when glasses are identified, the glasses can be divided in advance into frames and lenses, and the frames include upper edge, lower edge, outer edge, inner edge, middle bridge of the nose, and upper corner, etc. Specifically, as an optional embodiment, the facial commodity object includes glasses, and the commodity feature data includes at least one of upper edge feature data, lower edge feature data, inner edge feature data, outer edge feature data, middle bridge of the nose feature data, upper corner feature data, frame height, frame color, lens color, frame thickness, frame material, frame integrity, frame shape, and frame transparency. The embodiment of the present application can divide the facial commodity object into multiple substructures, and then extract the structural data of each substructure to obtain the facial commodity object features of the facial commodity object.

[0042] Specifically, the upper edge features of the glasses may include: a level representing the degree of the upper edge convex upward, such as the first level (most convex), the second level (secondary convex), the third level (smooth), the fourth level (flatter), the fifth level (upward), etc. corresponding to the upper edge. The lower edge features of the glasses may include: a level representing the degree of the lower edge concaving downward. The inner edge features of the glasses may include: a level representing the degree of the lower inner edge tilting outward, such as the first level (outward expansion), the second level (centering), the third level (inward cohesion), etc. corresponding to the inner edge. The outer edge features of the glasses may include: a level representing the degree of the lower outer edge tilting inward, such as the first level (vertical), the second level (inward retraction), the third level (inward inclusion), etc. corresponding to the outer edge. The nose bridge features of the glasses may include: a level representing the height of the nose bridge, such as the first level (high position), the second level (middle position), the third level (low position), etc. corresponding to the nose bridge, and may also include a fourth level representing the number of nose bridges (representing the presence of two nose bridges, one of which is located at the top of the frame). The upper corner features of the glasses may include: rounded corners, sharp corners, etc. The completeness of the frame of the glasses may include: full frame, half frame, etc. The transparency of the frame of the glasses may include: transparent, semi-transparent, etc. The shape of the frame of the glasses may include: square, rectangular, circular, oval, etc.

[0043] After acquiring the facial feature data and the product feature data, the processing end analyzes the facial product object according to the facial feature data and the product feature data in step 204 to obtain a product analysis result. The processing end may analyze the degree of matching between each product feature data of the facial product object and the facial feature of the user, and then determine the product analysis result in combination with the analysis result corresponding to each facial feature of the user. Specifically, as an optional embodiment, the facial product object is analyzed according to the facial feature data and the product feature data to obtain a product analysis result, including: analyzing each product feature data of the facial product object according to the facial feature data of the user to obtain a corresponding feature analysis result; and determining the product analysis result of the facial product object according to the feature analysis result corresponding to each facial feature data. The processing end may obtain the product analysis result in a scoring manner. Specifically, the processing end may analyze the feature score of each product feature data of the facial product object corresponding to the facial feature data according to a certain facial feature data of the user as the feature analysis result. Then, the product score of the facial product object corresponding to the entire face of the user is obtained as the product analysis result. For example, in the case where the facial product object is glasses, the degree of match between the user's facial features and the product feature data of different glasses can be analyzed to obtain the feature score of the corresponding face shape, and then the feature scores of the user's other facial features (such as nose features, eye features, etc.) are analyzed to obtain the product scores between the user and the different glasses. In addition to using the scoring method to determine the product analysis results, the embodiments of the present application can also use the rating method to determine the product analysis results. For example, the degree of match between the glasses and the user's facial features can be determined to be the first level to obtain the product analysis results.

[0044] After determining the product analysis result, the processing end, in step 206, screens out facial product objects that meet the preset conditions based on the product analysis result. The product analysis result may include a product score of the user corresponding to the facial product object, and the product score includes a feature score of each facial feature of the user corresponding to the facial product object. The processing end may screen out facial product objects that meet the preset conditions based on the product score and feature score of each facial product object. Specifically, the processing end may sort the facial product objects based on the product analysis result, and then screen them based on the sorting result. Specifically, as an optional embodiment, the screening out facial product objects that meet the preset conditions based on the product analysis result includes: sorting the facial product objects based on the product analysis result and a sorting rule, the sorting rule including the matching degree between the facial product object and at least one facial feature data of the user; and screening out facial product objects that meet the preset conditions based on the sorting result. The sorting rule may be pre-set at the processing end, and the sorting rule includes the matching degree between the facial product object and at least one facial feature of the user. The processing end can determine the sorting result of the facial product object corresponding to the user's overall facial feature data based on the product rating, and the processing end can determine the sorting result of the facial product object corresponding to the user's single facial feature data based on the feature rating in the product rating. Then, based on each sorting result, the facial product objects that meet the preset conditions are screened out for recommendation to the user. For example, the facial product objects with high rankings can be screened out and recommended to the user. For example, the processing end can screen out facial product objects with high rankings in product ratings based on the product ratings as facial product objects suitable for the user's overall face. The processing end can also screen out facial product objects with high feature scores based on feature ratings as facial product objects suitable for a certain feature of the user.

[0045] In addition, a corresponding sorting method can be determined based on the personalized features selected by the user to screen out commodity objects that are suitable for the features selected by the user. Specifically, as an optional embodiment, the method also includes: obtaining a commodity matching scheme selected by the user, and determining a sorting rule based on the commodity matching scheme, wherein the commodity matching scheme includes at least one facial feature data for screening facial commodity objects and / or at least one commodity feature data for screening facial commodity objects. A solution selection page may be provided on the user's terminal. The solution selection page may include a solution selection switch. The user may select the corresponding product matching solution through the solution selection switch. The product matching solution is used to determine the screening conditions. The product matching solution may include a universal matching solution and a personalized matching solution. The universal matching solution is used to screen facial product objects that have a high degree of matching with the user's overall or several (or one) pre-set facial features and / or conform to the product feature data in the universal matching solution. The personalized matching solution is used to screen facial product objects that have a high degree of matching with one or several facial features of the user and / or conform to the product feature data in the personalized matching solution. The personalized matching solution can be set according to the user's custom operation. For example, the user can select a personalized matching solution that includes facial features and metal frame features to screen glasses that are suitable for facial features and have metal frame features. In addition, in addition to being based on the user's customization, the personalized matching solution can also be determined based on the user's preference for facial products in a historical period. For example, if the user has frequently browsed glasses with metal frames in the past three days, the terminal can add the features of the metal frame to the product matching solution to perform product screening. In the embodiment of the present application, the user can select the corresponding product matching plan and upload it to the processing end. The processing end adopts the corresponding sorting rules according to the product matching plan, and then filters the facial product objects to facilitate the user's purchase.

[0046] After filtering out the facial commodity objects, the processing end may obtain the information corresponding to the facial commodity objects and display it to the user. Specifically, as an optional embodiment, the method further includes: obtaining the commodity link information and commodity description information of the filtered facial commodity objects as display information. The commodity description information is information describing the commodity, such as commodity pictures, commodity prices, commodity brands and other information. The commodity link information is used to indicate the commodity details page corresponding to the facial commodity object. The user can click on the commodity link information to enter the commodity details page to purchase the commodity. After filtering out the facial commodity objects that match the user's face, the processing end may obtain the commodity link information and commodity description information corresponding to the facial commodity objects as display information, and then display the display information to the user. In the case where the processing end is the user's terminal, the processing end may display the display information on the page. In the case where the processing end is the server, the processing end may send the display information to the terminal to display the display information to the user of the terminal.

[0047] In addition to displaying product description information and product link information, the embodiments of the present application can also display the reasons for recommending the product to the user. Specifically, as an optional embodiment, the method further includes: obtaining recommendation information corresponding to the screened facial product object based on the product analysis results; adding the recommendation information to the display information. The recommendation information can be understood as the recommendation reason for the facial product object, and the recommendation reason for the facial product object is determined based on the match between the product and the user's facial feature data. For example, the screened facial product object may only have a high degree of match (or a high score) with the user's facial features, and the facial product object has a low degree of match with other facial features of the user. In this case, the recommendation reason for the facial product object can be determined to be "modifying the face shape", and then the recommendation information is added to the display information for display to the user.

[0048] In an embodiment of the present application, the facial feature data of the user and the product feature data of the facial product object can be obtained, and then the facial feature data of the user and the product feature data of the facial product object can be matched and analyzed to obtain a product analysis result, and then screening can be performed based on the product analysis result to screen out facial product objects that are suitable for the user's facial features, and they can be recommended to the user to facilitate the user's purchase.

[0049] Based on the above embodiments, the present application also provides a data processing method, which can be executed by a processing terminal, such as Figure 3 As shown, the method includes:

[0050] Step 302: Acquire a product image of a facial product object, and extract product structure data of the facial product object in the product image.

[0051] Step 304: Determine the product feature data of the facial product object according to the product structure data. As an optional embodiment, the facial product object includes glasses, and the product feature data includes at least one of upper edge feature data, lower edge feature data, inner edge feature data, outer edge feature data, middle bridge of nose feature data, upper corner feature data, frame height, frame color, lens color, frame thickness, frame material, frame integrity, frame shape, and frame transparency.

[0052] Step 306: Obtain the user's facial image and identify the facial image to obtain facial feature data. As an optional embodiment, the facial feature data includes: at least one of face shape features, three-part and five-eye features, eye features, nose features, forehead features, eyebrow features, and skin color features.

[0053] Step 308: Analyze the product feature data of the facial product object based on the user's facial feature data to obtain corresponding feature analysis results.

[0054] Step 310: Determine the commodity analysis result of the facial commodity object according to the feature analysis result corresponding to each facial feature data.

[0055] Step 312: Sort the facial product objects according to the product analysis results and sorting rules, wherein the sorting rules include the matching degree between the facial product objects and at least one facial feature data of the user.

[0056] Step 314: Filter out facial product objects that meet preset conditions based on the sorting results.

[0057] Step 316: Obtain product link information and product description information of the filtered facial product object as display information.

[0058] Step 318: Obtain recommendation information corresponding to the filtered facial product objects based on the product analysis results.

[0059] Step 320: Add the recommendation information to the display information.

[0060] In an embodiment of the present application, a product image of a facial product object can be obtained, and the product structure data of the facial product object in the product image can be extracted to obtain product feature data of the facial product object. A facial image of a user is obtained, and facial feature data in the facial image is identified. After the facial feature data and product feature data are determined, the matching between each product feature data of the product object and each facial feature of the user is analyzed to obtain a feature analysis result, and further obtain a product analysis result. Then, based on the product analysis result, the facial products are sorted to obtain at least one sorting result, and then screened based on the sorting structure to obtain a product object suitable for the user. Then, the product link information, product description information and corresponding recommendation information of the screened facial product object are obtained as display information. The display information is then displayed to the user, and the user can purchase the product based on the display information.

[0061] In addition to analyzing the matching between each facial product and the user's facial features, the embodiment of the present application can also pre-set several facial products representing different types, and then determine the type that matches the user's facial features, and then recommend facial products of this type to the user. Specifically, based on the above embodiment, the embodiment of the present application also provides a data processing method that can be executed by a processing terminal, such as Figure 4 As shown, the method includes:

[0062] Step 402: Obtain the user's facial feature data and the product feature data of each type of facial product object.

[0063] Step 404: Analyze various types of facial commodity objects based on the facial feature data and the commodity feature data to obtain commodity analysis results.

[0064] Step 406: Determine the target type that meets the preset conditions based on the product analysis result, and obtain the facial product object of the target type.

[0065] The steps of the data processing method in the embodiment of the present application are similar to the steps of the method in the above embodiment. The specific implementation method can refer to the implementation method of the above embodiment, and will not be repeated here.

[0066] In an embodiment of the present application, the user's facial feature data and the product feature data of each type of facial product object can be obtained, wherein a representative facial product can be selected for each type. Then, the user's facial feature data and the product feature data of each type of facial product object are matched and analyzed to obtain a product analysis result, and then the product analysis result is filtered to filter out the target type that suits the user's facial features, and obtain the facial product object of the target type, and recommend it to the user to facilitate the user's purchase. In an embodiment of the present application, a small number of representative facial products can be set for each type, and a small number of facial products can be matched with the user's facial features, which can reduce the amount of data analyzed.

[0067] The embodiments of the present application can also be applied to facial product recommendation scenarios based on augmented reality (AR). AR technology is a technology that cleverly integrates virtual information with the real world. It widely uses multimedia, three-dimensional modeling, real-time tracking and registration, intelligent interaction, sensing and other technical means to simulate computer-generated virtual information such as text, images, three-dimensional models, music, and videos, and apply them to the real world. The two types of information complement each other, thereby achieving "enhancement" of the real world. The method of the embodiments of the present application can obtain the facial feature data of the user and the product feature data of the facial product object, and then analyze the degree of match between each facial product object and the facial features of the user to screen out facial product objects that are suitable for the user's facial features, and display them to the user in AR to facilitate the user's purchase. Specifically, on the basis of the above embodiments, the embodiments of the present application also provide a data processing method that can be executed by a processing end. The processing end can be understood as the user's terminal, such as Figure 5 As shown, the method includes:

[0068] Step 502: Take a facial image of the user and upload it. The facial image is used to determine facial feature data. The facial feature data is used to analyze product feature data of facial product objects to determine product analysis results. The product analysis results are used to screen out facial product objects that match the user's facial image.

[0069] Step 504: Receive try-on display information corresponding to the filtered facial product objects, the try-on display information including a facial image of a person trying on the facial product object and display information of the facial product object, the display information including product link information and product description information of the facial product object.

[0070] Step 506: Display a facial image of the person trying on the facial product object.

[0071] The steps of the data processing method in the embodiment of the present application are similar to the steps of the method in the above embodiment. The specific implementation method can refer to the implementation method of the above embodiment, and will not be repeated here.

[0072] In an embodiment of the present application, the processing end (the user's terminal) can take a facial image of the user and upload the facial image to the server. The server performs recognition based on the facial image, determines facial feature data, and then analyzes the matching of the user's facial feature data with the product feature data of each facial product object to obtain the product analysis result. Based on the product analysis result, the facial product object suitable for the user's facial features is screened out, and then the display information and virtual three-dimensional structure data of the screened facial product object are obtained, and the virtual three-dimensional structure data is tried on the user's facial image to generate the try-on display information, which is sent to the terminal. The terminal can display the facial image of the tried-on facial product object on the page. Among them, the virtual three-dimensional structure data can be understood as virtual information in AR technology. For example, in the case where the facial product object is glasses, the position of the user's eyes can be identified, and the virtual three-dimensional structure data of the glasses can be tried on the position of the user's eyes. The embodiment of the present application can use AR technology to provide users with a trial of virtual three-dimensional structure data, which can facilitate users to purchase. The embodiment of the present application can screen out multiple facial product objects and obtain multiple corresponding display information. Multiple display information can be displayed on the page of the user's terminal. The user can switch the virtual three-dimensional structure of different facial product objects by operating the multiple display information.

[0073] The embodiment of the present application can also obtain the user's preference for facial commodity objects, and filter the facial commodity objects according to the preference. Specifically, as an optional embodiment, the method also includes: obtaining the user's commodity matching plan, the commodity matching plan including at least one facial feature data for filtering facial commodity objects and / or at least one commodity feature data for filtering facial commodity objects; uploading the commodity matching plan to filter facial commodity objects that meet the commodity matching plan. A solution selection page may be provided on the user's terminal. The solution selection page may include a solution selection switch. The user may select the corresponding product matching solution through the solution selection switch. The product matching solution is used to determine the screening conditions. The product matching solution may include a universal matching solution and a personalized matching solution. The universal matching solution is used to screen facial product objects that have a high degree of matching with the user's overall or several (or one) pre-set facial features and / or conform to the product feature data in the universal matching solution. The personalized matching solution is used to screen facial product objects that have a high degree of matching with one or several facial features of the user and / or conform to the product feature data in the personalized matching solution. The personalized matching solution may be set according to the user's custom operation. For example, the user may select a personalized matching solution that includes facial features and metal frame features to screen glasses that are suitable for facial features and have metal frame features. In addition, in addition to being based on the user's customization, the personalized matching solution may also be determined based on the user's preference for products in a historical period. For example, if the user has frequently browsed glasses with metal frames in the past three days, the terminal may add the features of the metal frames to the product matching solution to perform product screening. In the embodiment of the present application, the user can select the corresponding product matching plan and upload it to the processing end. The processing end adopts the corresponding sorting rules according to the product matching plan, and then filters the facial product objects to facilitate the user's purchase.

[0074] In an embodiment of the present application, an IoT device that can capture a user's facial image and display commodity objects can also be used as a user's terminal to capture the user's facial image, determine the facial feature data corresponding to the facial image, and display the corresponding facial commodity image. For example, a smart beauty mirror can be used to obtain the user's facial image, determine the facial feature data of the facial image, and upload the facial feature data to the server (processing end) for analysis to screen out facial commodity objects that meet the user's facial features. The server then returns the relevant information of the screened facial commodity objects to the smart beauty mirror, and the display component of the smart beauty mirror displays the facial commodity objects. The user can try on the product by illuminating his or her face through the mirror surface of the smart beauty mirror. Specifically, the data processing method can be applied to an IoT device, wherein the IoT device includes an image acquisition component and a display component, such as Figure 6 As shown, the method comprises:

[0075] Step 602: Capture the user's facial image through the image acquisition component.

[0076] Step 604: determine facial feature data based on the facial image and upload it. The facial feature data is used to analyze the product feature data of the facial product object to determine a product analysis result. The product analysis result is used to screen out facial product objects that match the user's facial image.

[0077] Step 606: Receive the filtered facial product objects.

[0078] Step 608: Display the filtered facial product objects through the display component.

[0079] The steps of the data processing method in the embodiment of the present application are similar to the steps of the method in the above embodiment. The specific implementation method can refer to the implementation method of the above embodiment, and will not be repeated here.

[0080] In an embodiment of the present application, an IoT device (such as a smart makeup mirror) can take a user's facial image, extract facial feature data from the facial image, and upload it to a server (processing end). Based on the facial feature data, the server analyzes the matching of the user's facial feature data with the product feature data of each facial product object, obtains the product analysis result, and based on the product analysis result, selects facial product objects that are suitable for the user's facial features, and then sends the selected facial product objects to the IoT device. The user can illuminate his or her face through the mirror of the smart makeup mirror, and the IoT device can identify the user's facial display position, and display the selected facial product objects at the facial display position through the display component for trial wearing. For example, in the case where the facial product object is glasses, the position of the user's eyes can be identified, and the virtual information of the glasses can be displayed at the position of the user's eyes. The embodiment of the present application can use AR technology to provide users with virtual information for trial wearing, which can facilitate users to make purchases.

[0081] It should be noted that, for the method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present application are not limited by the described order of actions, because according to the embodiments of the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present application.

[0082] Based on the above embodiment, this embodiment further provides a data processing device, referring to Figure 7 , specifically it can include the following modules:

[0083] The feature data acquisition module 702 is used to acquire the facial feature data of the user and the product feature data of the facial product object.

[0084] The analysis result acquisition module 704 is used to analyze the facial commodity object according to the facial feature data and the commodity feature data to obtain a commodity analysis result.

[0085] The commodity object screening module 706 is used to screen out facial commodity objects that meet preset conditions according to the commodity analysis results.

[0086] In summary, in the embodiments of the present application, the facial feature data of the user and the product feature data of the facial product object can be obtained, and then the facial feature data of the user and the product feature data of the facial product object are matched and analyzed to obtain the product analysis result, and then screening is performed based on the product analysis result, so that facial product objects suitable for the user's facial features can be screened out, and facial products that are more suitable for the user can be recommended to the user, making it convenient for the user to purchase.

[0087] On the basis of the above embodiment, this embodiment further provides a data processing device, which may specifically include the following modules:

[0088] The product image acquisition module is used to acquire the product image of the facial product object and extract the product structure data of the facial product object in the product image.

[0089] The product image recognition module is used to determine the product feature data of the facial product object according to the product structure data. As an optional embodiment, the facial product object includes glasses, and the product feature data includes at least one of upper edge feature data, lower edge feature data, inner edge feature data, outer edge feature data, middle bridge of nose feature data, upper corner feature data, frame height, frame color, lens color, frame thickness, frame material, frame integrity, frame shape, and frame transparency.

[0090] The facial image recognition module is used to obtain the user's facial image and recognize the facial image to obtain facial feature data. As an optional embodiment, the facial feature data includes: at least one of face shape features, three-part and five-eye features, eye features, nose features, forehead features, eyebrow features, and skin color features.

[0091] The feature analysis result determination module is used to analyze the feature data of each product of the facial product object according to the facial feature data of the user to obtain the corresponding feature analysis result.

[0092] The commodity analysis result determination module is used to determine the commodity analysis result of the facial commodity object according to the feature analysis result corresponding to each facial feature data.

[0093] The commodity object sorting module is used to sort the facial commodity objects according to the commodity analysis results and sorting rules, wherein the sorting rules include the matching degree between the facial commodity objects and at least one facial feature data of the user.

[0094] The facial product object screening module is used to screen out facial product objects that meet preset conditions based on the sorting results.

[0095] The display information determination module is used to obtain the product link information and product description information of the filtered facial product object as display information.

[0096] The recommendation information acquisition module is used to obtain the recommendation information corresponding to the screened facial product objects according to the product analysis results.

[0097] The recommendation information adding module is used to add the recommendation information to the display information.

[0098] In an embodiment of the present application, a product image of a facial product object can be obtained, and the product structure data of the facial product object in the product image can be extracted to obtain product feature data of the facial product object. A facial image of a user is obtained, and facial feature data in the facial image is identified. After the facial feature data and product feature data are determined, the matching between each product feature data of the product object and each facial feature of the user is analyzed to obtain a feature analysis result, and further obtain a product analysis result. Then, based on the product analysis result, the facial products are sorted to obtain at least one sorting result, and then screened based on the sorting structure to obtain a product object suitable for the user. Then, the product link information, product description information and corresponding recommendation information of the screened facial product object are obtained as display information. The display information is then displayed to the user, and the user can purchase the product based on the display information.

[0099] Based on the above embodiment, this embodiment further provides a data processing device, referring to Figure 8 , specifically it can include the following modules:

[0100] The feature data determination module 802 is used to obtain the facial feature data of the user and the commodity feature data of various types of facial commodity objects.

[0101] The analysis result determination module 804 is used to analyze various types of facial commodity objects according to the facial feature data and the commodity feature data to obtain commodity analysis results.

[0102] The commodity object determination module 806 is used to determine the target type that meets the preset conditions according to the commodity analysis result, and obtain the facial commodity object of the target type.

[0103] In summary, in the embodiment of the present application, the user's facial feature data and the commodity feature data of each type of facial commodity object can be obtained, wherein a representative facial commodity can be selected for each type. Then, the user's facial feature data and the commodity feature data of each type of facial commodity object are matched and analyzed to obtain a commodity analysis result, and then the commodity analysis result is filtered to filter out the target type that is suitable for the user's facial features, and obtain the facial commodity object of the target type, and recommend it to the user to facilitate the user's purchase. In the embodiment of the present application, a small number of representative facial commodities can be set for each type, and a small number of facial commodities can be matched with the user's facial features, which can reduce the amount of data analyzed.

[0104] Based on the above embodiment, this embodiment further provides a data processing device, referring to Fig. 9 , specifically it can include the following modules:

[0105] The image data determination module 902 is used to capture the user's facial image and upload it. The facial image is used to determine facial feature data. The facial feature data is used to analyze the product feature data of the facial product object to determine the product analysis result. The product analysis result is used to screen out facial product objects that match the user's facial image.

[0106] The related information determination module 904 is used to receive the display information and virtual three-dimensional structure data of the filtered facial commodity objects, wherein the display information includes commodity link information and commodity description information of the facial commodity objects.

[0107] The related information display module 906 is used to display the display information and the facial image with the virtual three-dimensional structure data.

[0108] In summary, in the embodiment of the present application, the processing end (the user's terminal) can take the user's facial image and upload the facial image to the server. The server recognizes the facial image, determines the facial feature data, and then analyzes the matching of the user's facial feature data with the product feature data of each facial product object to obtain the product analysis result. According to the product analysis result, the facial product object suitable for the user's facial features is screened out, and then the display information and virtual three-dimensional structure data of the screened facial product object are obtained, and sent to the terminal. The terminal can display the display information on the page and try on the virtual three-dimensional structure data at the facial display position of the facial image. Among them, the virtual three-dimensional structure data can be understood as virtual information in AR technology. For example, in the case where the facial product object is glasses, the position of the user's eyes can be identified, and the virtual three-dimensional structure data of the glasses can be tried on the position of the user's eyes. The embodiment of the present application can use AR technology to provide users with a trial of virtual three-dimensional structure data, which can facilitate users to purchase. The embodiment of the present application can screen out multiple facial product objects and obtain multiple corresponding display information. Multiple display information can be displayed on the page of the user's terminal. The user can switch the virtual three-dimensional structure of different facial product objects by operating multiple display information.

[0109] Based on the above embodiment, this embodiment further provides a data processing device, which is applied to an Internet of Things device. The Internet of Things device includes an image acquisition component and a display component. Fig.10 , specifically it can include the following modules:

[0110] The image data acquisition module 1002 is used to acquire the user's facial image through the image acquisition component.

[0111] The image data analysis module 1004 is used to determine and upload facial feature data based on the facial image. The facial feature data is used to analyze the product feature data of the facial product object to determine the product analysis result. The product analysis result is used to filter out facial product objects that match the user's facial image.

[0112] The product object receiving module 1006 is used to receive the filtered facial product objects.

[0113] The product object display module 1008 is used to display the filtered facial product objects through a display component.

[0114] In an embodiment of the present application, an IoT device (such as a smart makeup mirror) can take a user's facial image, extract facial feature data from the facial image, and upload it to a server (processing end). Based on the facial feature data, the server analyzes the matching of the user's facial feature data with the product feature data of each facial product object, obtains the product analysis result, and based on the product analysis result, selects facial product objects that are suitable for the user's facial features, and then sends the selected facial product objects to the IoT device. The user can illuminate his or her face through the mirror of the smart makeup mirror, and the IoT device can identify the user's facial display position, and display the selected facial product objects at the facial display position through the display component for trial wearing. For example, in the case where the facial product object is glasses, the position of the user's eyes can be identified, and the virtual information of the glasses can be displayed at the position of the user's eyes. The embodiment of the present application can use AR technology to provide users with virtual information for trial wearing, which can facilitate users to make purchases.

[0115] The embodiment of the present application also provides a non-volatile readable storage medium, which stores one or more modules (programs). When the one or more modules are applied to a device, the device can execute instructions (instructions) of each method step in the embodiment of the present application.

[0116] The present application embodiment provides one or more machine-readable media, on which instructions are stored, and when executed by one or more processors, an electronic device executes one or more methods as described in the above embodiments. In the present application embodiment, the electronic device includes a server, a terminal device, and the like.

[0117] The embodiments of the present disclosure may be implemented as a device configured as desired using any appropriate hardware, firmware, software, or any combination thereof, and the device may include electronic devices such as a server (cluster), a terminal, etc. Fig.11 An exemplary apparatus 1100 that can be used to implement various embodiments described in this application is schematically shown.

[0118] For one embodiment, Fig.11 An exemplary apparatus 1100 is shown having one or more processors 1102, a control module (chip set) 1104 coupled to at least one of the (one or more) processors 1102, a memory 1106 coupled to the control module 1104, a non-volatile memory (NVM) / storage device 1108 coupled to the control module 1104, one or more input / output devices 1110 coupled to the control module 1104, and a network interface 1112 coupled to the control module 1104.

[0119] The processor 1102 may include one or more single-core or multi-core processors, and the processor 1102 may include any combination of general-purpose processors or special-purpose processors (such as graphics processors, application processors, baseband processors, etc.). In some embodiments, the device 1100 can be used as a server, terminal, or other device described in the embodiments of the present application.

[0120] In some embodiments, the apparatus 1100 may include one or more computer-readable media (e.g., memory 1106 or NVM / storage device 1108) having instructions 1114 and one or more processors 1102 combined with the one or more computer-readable media and configured to execute the instructions 1114 to implement a module to perform the actions described in the present disclosure.

[0121] For one embodiment, the control module 1104 may include any suitable interface controller to provide any suitable interface to at least one of the processor(s) 1102 and / or any suitable device or component in communication with the control module 1104 .

[0122] The control module 1104 may include a memory controller module to provide an interface to the memory 1106. The memory controller module may be a hardware module, a software module, and / or a firmware module.

[0123] The memory 1106 may be used, for example, to load and store data and / or instructions 1114 for the device 1100. For one embodiment, the memory 1106 may include any suitable volatile memory, such as a suitable DRAM. In some embodiments, the memory 1106 may include double data rate type four synchronous dynamic random access memory (DDR4 SDRAM).

[0124] For one embodiment, control module 1104 may include one or more input / output controllers to provide an interface to NVM / storage device 1108 and input / output device(s) 1110 .

[0125] For example, NVM / storage 1108 may be used to store data and / or instructions 1114. NVM / storage 1108 may include any suitable non-volatile memory (e.g., flash memory) and / or may include any suitable non-volatile storage device(s) (e.g., one or more hard disk drives (HDDs), one or more compact disk (CD) drives, and / or one or more digital versatile disk (DVD) drives).

[0126] NVM / storage device 1108 may include storage resources that are part of the device on which apparatus 1100 is installed, or it may be accessible to the device without being part of the device. For example, NVM / storage device 1108 may be accessed via (one or more) input / output devices 1110 over a network.

[0127] (One or more) input / output devices 1110 may provide an interface for the apparatus 1100 to communicate with any other appropriate device, and the input / output device 1110 may include a communication component, an audio component, a sensor component, etc. The network interface 1112 may provide an interface for the apparatus 1100 to communicate through one or more networks, and the apparatus 1100 may wirelessly communicate with one or more components of a wireless network according to any of one or more wireless network standards and / or protocols, for example, access a wireless network based on a communication standard, such as WiFi, 2G, 3G, 4G, 5G, etc., or a combination thereof for wireless communication.

[0128] For one embodiment, at least one of the processor(s) 1102 may be packaged together with the logic of one or more controllers (e.g., a memory controller module) of the control module 1104. For one embodiment, at least one of the processor(s) 1102 may be packaged together with the logic of one or more controllers of the control module 1104 to form a system-in-package (SiP). For one embodiment, at least one of the processor(s) 1102 may be integrated on the same die with the logic of one or more controllers of the control module 1104. For one embodiment, at least one of the processor(s) 1102 may be integrated on the same die with the logic of one or more controllers of the control module 1104 to form a system-on-chip (SoC).

[0129] In various embodiments, the device 1100 may be, but is not limited to, a terminal device such as a server, a desktop computing device, or a mobile computing device (e.g., a laptop computing device, a handheld computing device, a tablet computer, a netbook, etc.). In various embodiments, the device 1100 may have more or fewer components and / or a different architecture. For example, in some embodiments, the device 1100 includes one or more cameras, a keyboard, a liquid crystal display (LCD) screen (including a touch screen display), a non-volatile memory port, multiple antennas, a graphics chip, an application-specific integrated circuit (ASIC), and a speaker.

[0130] Among them, the main control chip can be used as a processor or control module in the detection device, sensor data, location information, etc. are stored in a memory or NVM / storage device, the sensor group can be used as an input / output device, and the communication interface may include a network interface.

[0131] An embodiment of the present application further provides an electronic device, comprising: a processor; and a memory, on which executable code is stored, and when the executable code is executed, the processor executes one or more methods described in the embodiments of the present application.

[0132] The embodiments of the present application also provide one or more machine-readable media on which executable codes are stored. When the executable codes are executed, the processor executes one or more methods described in the embodiments of the present application.

[0133] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0134] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0135] The present application embodiment is described with reference to the flowchart and / or block diagram of the method, terminal device (system) and computer program product according to the embodiment of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, and the combination of the process and / or box in the flowchart and / or block diagram can be realized by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing terminal device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device produce a device for realizing the function specified in one process or multiple processes in the flowchart and / or one box or multiple boxes in the block diagram.

[0136] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0137] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce computer-implemented processing, so that the instructions executed on the computer or other programmable terminal device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0138] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present application.

[0139] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0140] The data processing method, the data processing device, the electronic device and the storage medium provided by the present application are introduced in detail above. The principles and implementation methods of the present application are explained in this article by using specific examples. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A data processing method, characterized in that: The method includes: Obtain user's facial feature data; Obtain a product image of a facial product object, and extract product structure data of the facial product object in the product image; Determining commodity feature data of the facial commodity object according to the commodity structure data; Analyze the feature scores of each product feature data of the facial product object corresponding to the facial feature data according to the facial feature data of the user, and use the feature scores as feature analysis results; Determine, based on the feature scores corresponding to the facial feature data, a product score of the facial product object corresponding to the entire face of the user as a product analysis result of the facial product object; According to the product analysis result, facial product objects meeting preset conditions are screened out.

2. The method according to claim 1, characterized in that Also includes: Get the product link information and product description information of the filtered facial product object as display information.

3. The method according to claim 2, characterized in that Also includes: According to the product analysis result, obtaining recommendation information corresponding to the screened facial product objects; The recommendation information is added to the display information.

4. The method according to claim 1, characterized in that: The steps of obtaining facial feature data include: Obtain the user's facial image, and recognize the facial image to obtain facial feature data.

5. The method according to claim 1, characterized in that The step of screening out facial product objects that meet preset conditions based on the product analysis results includes: Sorting facial product objects according to the product analysis results and a sorting rule, wherein the sorting rule includes a matching degree between the facial product objects and at least one facial feature data of the user; Based on the sorting results, filter out facial product objects that meet the preset conditions.

6. The method according to claim 5, characterized in that The method further comprises: A product matching scheme of the user is obtained, and a sorting rule is determined according to the product matching scheme, wherein the product matching scheme includes at least one facial feature data for screening facial product objects and / or at least one product feature data for screening facial product objects.

7. The method according to claim 1, characterized in that The facial product object includes glasses, and the product feature data includes at least one of upper edge feature data, lower edge feature data, inner edge feature data, outer edge feature data, middle nose bridge feature data, upper corner feature data, frame height, frame color, lens color, frame thickness, frame material, frame integrity, frame shape, and frame transparency.

8. The method according to claim 1, characterized in that The facial feature data includes: at least one of face shape features, three-part and five-eye features, eye features, nose features, forehead features, eyebrow features, and skin color features.

9. A data processing method, characterized in that: include: Obtain user's facial feature data; Obtain a product image of a facial product object, and extract product structure data of the facial product object in the product image; Determining commodity feature data of each type of facial commodity object according to the commodity structure data; Analyze the feature scores of each product feature data of the facial product object corresponding to the facial feature data according to the facial feature data of the user, and use the feature scores as feature analysis results; Determine, based on the feature scores corresponding to the facial feature data, a product score of the facial product object corresponding to the entire face of the user as a product analysis result of the facial product object; According to the commodity analysis result, a target type that meets preset conditions is determined, and a facial commodity object of the target type is obtained.

10. A data processing method, characterized in that: include: Taking a facial image of a user and uploading it, the facial image is used to determine facial feature data, the facial feature data is used to analyze the feature scores of each product feature data of a facial product object corresponding to the facial feature data based on the facial feature data of the user, taking the feature scores as feature analysis results, determining the product scores of the facial product objects corresponding to the entire face of the user based on the feature scores corresponding to each facial feature data as product analysis results of the facial product objects, the product analysis results are used to screen out facial product objects that match the facial image of the user, the product feature data is determined based on product structure data, and the product structure data is extracted from the facial product objects in the product image; Receive try-on display information corresponding to the filtered facial commodity object, the try-on display information including a facial image of a person trying on the facial commodity object and display information of the facial commodity object, the display information including commodity link information and commodity description information of the facial commodity object; A facial image of the object trying on the facial merchandise object is displayed.

11. The method according to claim 10, characterized in that Also includes: Acquire a product matching scheme of the user, wherein the product matching scheme includes at least one facial feature data for screening facial product objects and / or at least one product feature data for screening facial product objects; The product matching scheme is uploaded to filter facial product objects that meet the product matching scheme.

12. A data processing method, characterized in that: Applied to an Internet of Things device, the Internet of Things device includes an image acquisition component and a display component, and the method includes: Collecting a user's facial image by the image acquisition component; Determine facial feature data based on the facial image and upload the facial feature data, the facial feature data being used to analyze feature scores of each product feature data of a facial product object corresponding to the facial feature data based on the facial feature data of the user, taking the feature scores as feature analysis results, determining a product score of the facial product object corresponding to the entire face of the user based on the feature scores corresponding to each facial feature data as a product analysis result of the facial product object, the product analysis result being used to screen out facial product objects that match the facial image of the user, the product feature data being determined based on product structure data, the product structure data being extracted from the facial product object in the product image; Receive the filtered facial product objects; The filtered facial product objects are displayed through the display component.

13. A data processing device, characterized in that: include: A feature data acquisition module is used to acquire the user's facial feature data; Acquire a product image of a facial product object, extract product structure data of the facial product object in the product image, and determine product feature data of the facial product object based on the product structure data; An analysis result acquisition module is used to analyze the feature scores of each commodity feature data of the facial commodity object corresponding to the facial feature data according to the facial feature data of the user, and use the feature scores as the feature analysis results; and determine the commodity score of the facial commodity object corresponding to the entire face of the user according to the feature scores corresponding to each facial feature data, as the commodity analysis result of the facial commodity object; The product object screening module is used to screen out facial product objects that meet preset conditions based on the product analysis results.

14. A data processing device, characterized in that: include: A feature data determination module, used to obtain the user's facial feature data; Acquire a product image of a facial product object, extract product structure data of the facial product object in the product image, and determine product feature data of each type of facial product object based on the product structure data; An analysis result determination module is used to analyze the feature scores of each commodity feature data of the facial commodity object corresponding to the facial feature data according to the facial feature data of the user, and use the feature scores as the feature analysis results; and determine the commodity score of the facial commodity object corresponding to the entire face of the user according to the feature scores corresponding to each facial feature data, as the commodity analysis result of the facial commodity object; The commodity object determination module is used to determine the target type that meets the preset conditions according to the commodity analysis result, and obtain the facial commodity object of the target type.

15. A data processing device, characterized in that: include: An image data determination module is used to take a facial image of a user and upload it, wherein the facial image is used to determine facial feature data, wherein the facial feature data is used to analyze a feature score of each product feature data of a facial product object corresponding to the facial feature data based on the facial feature data of the user, and the feature score is used as a feature analysis result. According to the feature score corresponding to each facial feature data, a product score of the facial product object corresponding to the entire face of the user is determined as a product analysis result of the facial product object, wherein the product analysis result is used to screen out facial product objects that match the facial image of the user, wherein the product feature data is determined based on product structure data, and the product structure data is extracted from the facial product object in the product image; A related information determination module is used to receive the try-on display information corresponding to the screened facial commodity object, the try-on display information including the facial image of the person trying on the facial commodity object and the display information of the facial commodity object, the display information including the commodity link information and the commodity description information of the facial commodity object; The related information display module is used to display the facial image of the person trying on the facial product object.

16. A data processing device, characterized in that: Applied to an Internet of Things device, the Internet of Things device includes an image acquisition component and a display component, and the device includes: An image data acquisition module, used to acquire a user's facial image through the image acquisition component; An image data analysis module, configured to determine and upload facial feature data based on the facial image, wherein the facial feature data is used to analyze, based on the facial feature data of the user, a feature score of each product feature data of a facial product object corresponding to the facial feature data, and use the feature score as a feature analysis result, and determine, based on the feature score corresponding to each facial feature data, a product score of the facial product object corresponding to the entire face of the user as a product analysis result of the facial product object, wherein the product analysis result is used to screen out facial product objects that match the facial image of the user, wherein the product feature data is determined based on product structure data, and the product structure data is extracted from the facial product object in the product image; A product object receiving module, used for receiving the filtered facial product objects; The product object display module is used to display the filtered facial product objects through the display component.

17. An electronic device, characterized in that: include: processor; and A memory having executable codes stored thereon, which, when executed, cause the processor to perform the method according to one or more of claims 1-12.

18. One or more machine-readable media having executable codes stored thereon, which, when executed, cause a processor to perform the method of one or more of claims 1-12.

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